The integrated circuit industry has, since its inception, maintained a remarkable growth rate by driving increased device functionality at lower cost. Leading edge devices today provide the computing power of computers that used to occupy entire rooms at a mere fraction of the cost. Many of today's low-cost consumer devices include functionality that only a few years ago was unavailable at any cost, such as video cell phones, ultra-portable media players, and wireless or ultra-wideband Internet devices. One of the primary enabling factors of this growth has been the ability of optical lithography processes to steadily decrease the smallest feature size that can be patterned as part of the integrated circuit pattern. This steady decline in feature size and cost while at the same time printing more features per circuit is commonly referred to as “Moore's Law” or the lithography “roadmap.”
The lithography process involves creating a master pattern on a mask or reticle, then replicating that pattern faithfully onto the device wafers. Typically the master pattern is projected onto a photosensitive film deposited on the top surface of the product wafers; this film is referred to as “photoresist” or simply “resist.” Projection is typically accomplished using an exposure tool usually referred to as a “scanner” or “stepper.” Most exposure tools in use today demagnify the master pattern by a factor of four or five times; this reduction ratio is often referred to by the incongruous phrase “magnification ratio.” For a feature intended to be 65 nm wide at the wafer level, e.g., the corresponding feature would be on the order of 260 nm wide at the reticle level. This difference in feature sizes between the reticle level and the wafer level is often implied, and for the remainder of this application, the features on the reticle will be referred to by their wafer-level dimensions, with the understanding that they are sized appropriately at the reticle level to produce the stated dimensions at the wafer level. As a result, a “65 nm feature on the reticle,” e.g., is understood to mean a “feature of the appropriate size at the reticle level to produce a 65 nm resist feature at the wafer level.”
Because of the highly non-linear nature of the pattern transfer process described in more detail below, not every individual feature on the reticle results in a wafer-level pattern in which the size is exactly equal to the reticle-level pattern size divided by the reduction ratio. This non-linearity is a key reason for the growing number of measurements needed to characterize the pattern transfer process, as well as for the growing number of patterns that need to be modified at the reticle level through the addition of optical proximity correction (OPC) and/or sub-resolution assist features (SRAFs) such as serifs and/or scattering bars.
The imaging system of the exposure tool, including all of the illumination and projection optics, as well as sophisticated electro-mechanical systems for aligning and moving the reticle and wafer relative to each other play a critical role in determining how well the master pattern is replicated. Any imperfections in the master pattern due to errors in the reticle manufacturing process or in the replication of the master pattern due to imperfections or aberrations in the exposure tool will reduce the quality and fidelity of the replicated patterns on the wafer, resulting in the devices not performing as intended.
A critical parameter of interest in qualifying the fidelity of the replicated images is the “critical dimension” of the pattern. The critical dimension is intended as a metric of the width of the features printed in the photoresist layer on the wafer. Since the resist patterns have finite thickness, the critical dimension is actually a two-dimensional measurement applied to a three-dimensional feature. Typically critical dimension is supposed to represent the width of the most critical features (usually the smallest geometries) in the device, measured at the base of the three-dimensional profile. In practice, it is often difficult to measure the resist width at the resist-substrate interface, and suitable proxies are employed to represent the critical dimension depending on which tools are used for the measurement. In common parlance, the term critical dimension is now used to represent almost any line-width measurement performed on the resist pattern.
At feature sizes below 100 nm, which are common today, the control of the critical dimensions on product wafers requires ever increasing amounts of critical dimension data and increasingly sophisticated process analysis and correction algorithms. In earlier generations of technology, typically only one or at most two process control inputs (dose and possibly focus) would be adjusted to control the printed critical dimensions relative to a desired target. In typical processes, only a few points across the wafer and at most one or two points across the field might be measured and controlled. Today, the number and the type of data collected have increased dramatically. Hundreds or thousands of points are often measured on tool and process characterization wafers to set up the exposure tool and process. Fewer points are available on product wafers due to limitations of available space for test structures on the device and the need to produce results in a short time, but the number of data points measured in production today is many times larger than the number that was measured a few years ago. Critical dimensions of different feature types (e.g., target dimension, pitch, and shape) are often measured at multiple points across the field, and many more adjustments may be made to the process to correct not only the mean-to-target offset but also the total critical dimension distribution across the field, across the wafer, and across the different feature types.
Current methods for collecting critical dimension data across the full field of an exposure tool are too time consuming and are usually limited to a very small number of measurement locations and/or features. An “image sensor array” was used in a new approach described in U.S. Pat. Nos. 6,828,542, 6,803,554, and 6,806,456, the subject matters of which are hereby incorporated by reference in their entirety. Such an image sensor array can measure the projected aerial image in-situ with several million sampling points across the field of the exposure tool, i.e., at the focal plane of a lithography exposure tool. An image sensor array with similar functionality may also be integrated within the wafer stage or the wafer chuck of the exposure system. From the data delivered by the in-situ image sensor array, printed critical dimensions may be predicted through a calibrated resist model, or image parameters such as contrast of edge slope may be analyzed directly. The vast increase in data volume made available by a large area image sensor array covering the complete exposure field of an exposure tool enables new methods of process and tool monitoring and process control, using either monitor or product reticles.
Monitor reticle applications of an in-situ aerial image sensor array may include monitoring and determining corrections for a large number of system parameters that affect imaging quality. These parameters include, e.g., focal plane variations of the exposure tool or other errors and changes in the illumination and/or projection optical systems that may cause unacceptably large variations in critical dimension distributions or other image parameters as a function of position within the exposure field and/or feature type. Examples of such errors may include, e.g., spherical aberration, astigmatism, focal plane curvature, and/or de-centering or incorrect partial coherence of the illumination apertures. These types of errors may escape detection if only a limited number of feature types at a limited number of points are evaluated. The use of a monitor reticle—with test structures laid out on a grid that matches the regular grid of individual image sensor elements of the image sensor array—maximizes the number of samples and pattern types that can be simultaneously measured. With the massive data volumes enabled by the new sensor technology, a large number of image system parameters can be uniquely addressed and unambiguously monitored in detail.
Product reticle applications of an in-situ aerial image sensor array involve various methods to sample critical dimensions or other image parameters across the reticle. The data sampling and data acquisition may be optimized to most effectively predict the full critical dimension distribution and other imaging performance across the exposure field. Any measured data will result from the combined effect of the specific combination of reticle and exposure tool being tested. The reticle's critical dimension variations or two-dimensional pattern shape variations on the reticle tend to have highly non-linear effects on the patterns formed at the image plane. The variation there may depend on the magnitude of the reticle variation, the nominal target shape and size, the local environment on the reticle near the feature in question, and the exposure and focus conditions or other optical parameters of the exposure tool. Critical dimension errors at the reticle level may result in very different critical dimension errors at the wafer level, depending on where in the field the errors occur and exactly what types of features are being patterned. This non-linearity is often referred to as Mask Error Factor (MEF) or Mask Error Enhancement Factor (MEEF), although in fact it is neither a simple multiplicative “factor” but a complex function of the pattern, the imaging tool, and the process conditions.
Consequently, verifying and predicting correctly the imaging performance of an actual production reticle is generally a challenging task. It is virtually impossible to test directly with sufficient density of sampling points on printed wafers whether the vast amount of OPC modifications applied to the reticle in a modern device design produce the desired edge placements and critical dimension values at every point. The actual patterning performance will depend not only on the thoroughness of the OPC design but also on the exact physical properties of the mask after being manufactured, the exact properties of the exposure tool illumination and projection optics, and the exact properties of resist processing. The use of an image sensor array based on the disclosures of U.S. Pat. Nos. 6,828,542, 6,803,554, and 6,806,456 significantly improves this situation by assessing directly the imaging performance at the focal plane while including all real mask and exposure tool effects but excluding additional uncertainties of resist processing properties (that can be separately calibrated to a model).
The image sensor array technology enables an entirely new method of qualifying the wafer-level critical dimension distributions and OPC performance by collecting millions of measurements within a few minutes, sampling different feature types at many locations across the field, and creating an exhaustive prediction of the wafer level image quality and the critical-dimension distribution that result from the particular combination of the reticle and the exposure system being measured and qualified by the image sensor array. The relatively short data acquisition time required also enables taking data at scheduled time intervals, e.g., on a regular preventive maintenance cycle, without a large impact on tool availability. This data may then be utilized to determine and monitor any process drifts over time, predict process corrections that optimize the common process window, or feed into existing statistical process control (SPC) systems.
However, the image sensor array itself introduces a new, additional source of uncertainty and variations due to possible non-perfect flatness of the image sensor array that is in practice hard to avoid completely. Due to topography of the image sensor array, each of the image sensor elements will sample the projected image at a slightly different focal position, and therefore a finite part of, e.g. the critical dimension non-uniformity, computed from the sensor data will actually be related to sensor non-flatness rather than to the exposure projection tool or the reticle properties. Consequently, an actual production wafer processed on the tool would not experience exactly the same critical dimension distribution as measured by the image sensor array, so the effectiveness of the image sensor array data for verifying across-reticle critical dimension variations or directly determining optimal process corrections would be limited. This same drawback exists both for production and monitor reticles; the true nature of the critical dimension non-uniformity induced by the reticle and the exposure tool is convolved with variations induced by the detector non-flatness, resulting in a possibly inaccurate picture of the imaging performance of the exposure tool.
The basic method of collecting data and forming high-resolution images employed in one embodiment of the present invention is described in U.S. Pat. Nos. 6,828,542, 6,803,554, and 6,806,456. With reference to FIG. 1, in one embodiment disclosed in the U.S. Pat. No. 6,828,542 patent, an image sensor array 106 includes a plurality of image sensor elements 200, including 200ax, to 200hx (x=1 to 8), that measure, sense, detect and/or collect incident energy or radiation. Image sensor array 106 is preferably embedded in an image sensor unit that is capable of being loaded into the wafer stage of an exposure tool.
In those instances where the dimensions of the active areas of image sensor elements 200 are too large to provide a desired or required spatial resolution, it may be necessary to limit, restrict, and/or reduce these sensor cells' active areas that are exposed. Hence, image sensor array 106 may include a patterned opaque film 204 that impedes, obstructs, absorbs, and/or blocks passage of photons or light of a given wavelength (that is, at the wavelength to be measured, sensed or detected by image sensor elements 200). Opaque film 204 includes apertures 206, including 206ax to 206hx (x=1 to 8), so that active areas of image sensor elements 200 are exposed only at apertures 206. As such, the spatial resolution of the energy measured by image sensor elements 200 is enhanced or improved because the portion or area of each image sensor element 200 that is effectively exposed to and/or measures, senses, detects, and/or collects energy or radiation is limited or restricted. Generally, image sensor elements 200 as well as any resolution enhancing measures, e.g., small apertures 206 formed in a light-blocking layer on top of image sensor elements 200, will be arranged on a very regular two-dimensional grid. A single exposure of image sensor array 106 is defined as a “frame.”
FIG. 2 shows a portion of the same image sensor array 106 as in FIG. 1. Here, only image sensor elements 200ax to 200gx (x=1 to 7) are shown. The multiple overlapping aperture positions 202a11 to 202a13 schematically represent the multiple lateral exposures of the image sensor element 200a1, where each exposure is offset by less than the size of the aperture 206a2 (shown in FIG. 1). The multiple overlapping images produced by the lateral exposures of the image sensor element 200a1 are combined to form a large image of stitched images. Such a large combined image is referred to as a “patch.”
FIG. 3A shows a single “patch” 310 composed of 16×18 overlapping exposures of a single aperture. Each individual exposure (represented by, e.g., a single circle 312) is referred to as a “pixel.” FIG. 3B shows a “sub-patch,” 320 which is a sub-group of exposures within a patch 310 composed of 3×3 overlapping exposures of a single aperture.
As mentioned above with reference to FIG. 1, image sensor array 106 consists of an array of individual image sensor elements 200 on a typically regular, rectangular grid. As illustrated in FIGS. 2 and 3, a set of high resolution image patches 310 (one for each image sensor element) is generated by repeated exposures of image sensor array 106 at the focal plane of the exposure tool, with small, lateral steps 290 (in the horizontal direction x) and 291 (in the vertical direction y) programmed between subsequent exposures, such that the locations of the resolution enhancing aperture cover a contiguous area of the projected image.
From the collected data samples of each image sensor element 200, a high-resolution image can then be reconstructed that covers the range of programmed lateral steps in x and y directions. The image sensor array may have several millions of image sensor elements, i.e., several million patches may be recorded in parallel. As the images are constructed from subsequent individual exposures over time, the projection conditions such as focus need to be kept constant during the data acquisition for one set of patches, using the existing, precise feedback controls of the exposure system.
FIG. 4 shows a flowchart of method steps for a prior art technique for image data preprocessing prior to image formation to reduce noise or errors in the data captured by image sensor array 106. In step 410, overlapping frames are collected over the full field of the exposure tool. In step 412, the frames are conditioned by correcting small errors in the offsets between frames on a full-frame basis. Overall intensity of each frame may also be corrected based on independent exposure data taken while the frame was being exposed. In step 414, patches are assembled using data from the conditioned frames produced in step 412. In step 416, the image patches are conditioned, where the conditioning includes noise reduction, smoothing, and classification on a patch-by-patch basis.
FIG. 5 schematically depicts an image sensor unit 524 including image sensor array 106 being exposed in an exposure tool at one particular focus offset. The exposure tool includes a mirror 512, a light source 514 to generate light 516 at a certain exposure wavelength, illumination optics 518, projection optics 522, and a chuck 526. Chuck 526 secures image sensor unit 524 in a fixed location using, for example, electrostatic or vacuum forces. The optics of the exposure tool interact with a mask 520 to project an aerial image onto image sensor array 106 in image sensor unit 524. In one embodiment, mask 520 contains the patterns to be replicated or printed onto a wafer during integrated circuit manufacturing. In another embodiment, mask 520 contains test patterns that are designed to evaluate the optical characteristics of the exposure tool. In one embodiment, image sensor unit 524 includes a processor/controller that implements data processing and analysis algorithms to process data captured by image sensor array 106. In another embodiment, the processor/controller is remote from image sensor unit 524 and is in communication with image sensor unit 524.